Lead Software Engineer – AI Platform [T500-30562]

About CIBC:

CIBC is a leading North American bank, with a history of more than 150 years of living our purpose - to help make your ambition a reality. Client relationships are at the center of our strategy, and our growth is enabled by a highly engaged and connected global team. From digital banking to community impact, we’re proud to drive progress for our clients and our communities. Recognized for our culture, award-winning innovation and community investment, CIBC continues to evolve by putting people and progress at the centre of everything we do.

About CIBC India:

CIBC India is a technology and operations hub in Hyderabad, where you’ll be part of our highly engaged and global team, and play a central role in supporting our growth. Whether you’re driving innovation in digital banking or streamlining client onboarding, you’ll be part of a culture recognized for excellence and investment in people. At CIBC India, people and progress are at the center of what we do: you’ll develop skills, collaborate with industry leaders, and see your ideas realized in a culture that values progress and belonging. We provide cutting-edge resources, ongoing learning, and a supportive environment where people come first. If you’re ready to create meaningful change and build your future, CIBC India is where your ambition meets opportunity.

What CIBC India Offers:

At CIBC India, your goals are a priority. We start with your strengths and ambitions and strive to create opportunities to tap into your potential. We aspire to give you a career that goes well beyond your compensation.

We work to recognize you in meaningful, personalized ways including competitive fixed pay, performance-based incentive programs, a family-first benefits program, employer contributions for your retirement, attractive time off and leave offerings, wellbeing support, and MomentMakers, our social, points-based recognition program.

Our spaces and technological toolkit will make it simple to bring together great minds to create innovative solutions that make a difference for our clients worldwide

We cultivate a culture where you can express your ambition through initiatives like Purpose Day, a paid day off dedicated for you to use to invest in your growth and development.

BUSINESS UNIT DESCRIPTION:

The Capital Markets Technology Team at CIBC is responsible for delivering advanced technology solutions that drive the success of the bank's Capital Markets business. This team encompasses specialized groups, including Derivatives Technology, Capital Markets Data Analytics, Electronic Trading, Fixed Income, FX, and Risk Management Software, Equities Technology etc each playing a vital role in supporting efficient, secure, and scalable trading and analytics platforms. By developing and maintaining robust systems for derivatives including sophisticated risk management software essential for monitoring, analyzing, and mitigating derivatives risk enabling high-performance electronic trading, providing comprehensive technology for fixed income and foreign exchange trading, and delivering actionable insights through advanced data analytics, the team ensures operational excellence, regulatory compliance, and superior client service. Through continuous innovation and alignment with strategic business objectives, the Capital Markets Technology Team empowers CIBC to manage risk effectively, respond to market opportunities, and deliver exceptional value to clients.

JOB PURPOSE:

Position summary:

• The team: You will join a senior team building CIBC's agentic AI platform for Capital Markets. As a Lead Software Engineer on the AI Platform, you will design, build, and operate the reusable services that give AI agents and applications reliable, secure access to structured and unstructured data.
• The role: A hands-on role that combines individual contribution with technical leadership: design ownership, code reviews, and mentoring. You will work across ingestion, search, retrieval APIs, metadata, caching, and evaluation, using Python, FastAPI, Qdrant, Azure AI Search, Databricks, LangGraph, Pydantic, and MLflow.
• Who we are looking for: Engineers with a strong track record of delivering production software at scale and hands-on experience with search and retrieval systems.
• Growth: As the platform grows, the role offers scope to expand into semantic layers over risk and PnL data, knowledge graphs, real-time data flows, and agentic workflows.

Responsibilities:

• Delivery: Write, review, test, and release production code every day at a high pace, without compromising quality.
• Technical leadership: Lead technical design for the services you own, set the quality bar through code reviews, and mentor other engineers.
• Ownership: Own large modules and features end to end, turning ambiguous requirements into frequent production releases.
• AI-assisted development: Use AI coding assistants to accelerate delivery, while critically reviewing generated code for correctness, security, and maintainability.
• Ingestion and retrieval services: Build reusable ingestion and retrieval services for unstructured documents and structured data, from parsing and indexing through to context assembly.
• APIs and agent tools: Define clear APIs, metadata schemas, and structured outputs, and expose retrieval as tools that AI agents can call.
• Retrieval quality: Measure and improve retrieval quality (including precision, recall, and hallucination reduction), latency, and cost against clear targets, using techniques such as hybrid search, reranking, and caching.
• Traceability: Ensure retrieval is accurate, context-aware, and auditable, so answers can be traced back to their sources.
• Reliability: Run services reliably at scale with automated testing, CI/CD, containerized deployment, observability, and failure recovery.
• Security & governance: Build access controls, data lineage, and safe handling of sensitive data into every retrieval path.
• Collaboration: Work closely with platform, data, security, and front-end teams across India and the UK, including some overlap with UK working hours.
• Engineering standards: Document designs and decisions clearly, and help shape the team's engineering standards.

KNOWLEDGE & SKILLS:

You bring 9+ years of software engineering experience. You have personally built and delivered multiple production software systems, including at least one that was enterprise-scale, high-volume, or business-critical, with robust design, comprehensive automated testing, operational readiness, and sustained production support. Be ready to explain your own technical contribution, the trade-offs you made, the scale involved, and the measurable outcomes.

Must-have skills:

• Python software engineering: Designing maintainable Python services, APIs, and data pipelines (e.g., FastAPI, Pydantic); typing, async/concurrency, and error handling; testing strategy (unit, integration, and contract tests); reviewing code for correctness and maintainability.
• Search, retrieval, and RAG: Indexing, chunking, embeddings, vector and hybrid (keyword + vector) search, metadata filtering, and reranking; applying access controls before results are ranked; measuring retrieval quality (precision, recall, groundedness) and improving it.
• Production engineering and reliability: Linux and shell, Docker, CI/CD; logging, metrics, and tracing; timeouts, retries, rate limits, and graceful degradation when a dependency fails; diagnosing and recovering from production incidents.
• System design and technical leadership: Designing a service end to end and defending the trade-offs (scale, latency, cost, failure modes); setting measurable targets and proving improvements; leading design and code reviews; mentoring engineers.
• LLM application engineering: Using LLM and embedding APIs; prompt and context design, structured outputs, and tool/function calling (e.g., MCP); evaluating outputs; cost and latency trade-offs; guarding against hallucination and prompt injection.
• AI-assisted software development: Daily use of AI coding agents (e.g., GitHub Copilot, Claude Code) to plan, build, and test faster, with the judgement to catch low-quality generated code, unnecessary churn, weak abstractions, security defects, and inadequate tests before they reach production.
• Data integration and governance: Combining structured and unstructured data from multiple sources; schemas, metadata, provenance, and lineage; handling sensitive data and enforcing entitlements.
• Learning agility: The ability to learn unfamiliar technologies and domains quickly.

Good-to-have skills:

• RAG in production: Hands-on experience running RAG in production, including retrieval evaluation.
• Our stack: Experience with FastAPI, Qdrant, Azure AI Search, Databricks, LangGraph, Pydantic, or MLflow.
• Azure: Building on Azure, including containers, Kubernetes, and identity-based access.
• Document parsing: Extracting content from PDFs, tables, and scanned documents (OCR).
• Semantic models and knowledge graphs: Designing semantic models, metadata systems, or knowledge graphs.
• Agent platforms: Agent frameworks and multi-agent workflows, or exposing platform services to AI agents as reusable tools.
• Capital markets: Familiarity with capital-markets data (such as trades, curves, surfaces, risk, and PnL), or experience delivering software in another complex, regulated domain.

Preferred: Bachelor's degree or higher in Computer Science or a related field, or equivalent practical experience.

COMPLIANCE REQUIREMENTS/RESPONSIBILITIES:

As an employee of CIBC, the incumbent must comply with all applicable CIBC and Line of Business policies, standards, guidelines and controls.

WORKING CONDITIONS:

This role operates within a normal office environment with little exposure to adverse working conditions. At CIBC India we enable the work environment most optimal for you to thrive in your role. Details on your work arrangement (including on-site and remote work) will be discussed at the time of your interview.

Privacy:

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